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Abstracts

Reliability of electrical appliances is long term observed parameter. There has been always conflict of interest; however the idea conflict is still sharpening. While end users require reliable operation (especially continuous energy supply), operators of power apparatus face reduction of funds for the repair and maintenance. Managers form their economical point of view try to reduce costs of new assets and operating costs of current assets. This leads to increasing demands on diagnostics and prognostics. As physical, empirical and statistical models are involved, it is possible to predict the behavior of operated assets and though to plan the service activities. The more precise these models are, the more accurate is the prognosis.
For prognosis of insulation system reliability, usually empirical and statistical models are involved. The empirical part came from accelerated aging tests. One or more degradation mechanisms are affecting the samples under test. The level of degradation factors must be elevated, so the end of life is achieved in significantly shorter time, than in real operation. So called endurance curves are obtained and sample performance in lower stress is estimated. The paper presents completion of such empirical tests with probability calculations. As there is always variation between samples and also variation caused by manufacturing process, mathematical statistics helps in lifetime calculations and brings the quantification of error and reliability.